How to simulate a starting queue before opening times in a Simulation process with Simpy?

I am studying SimPy and I came across this interesting tutorial that allows to simulate a queue in a bank.

I wanted to know if it is possible and how to create an initial queue.

Let's assume that the bank opens at 09:00 but we have already 20 customers waiting to be served + the other that will come with the defined probabilistic arrival rate.

How to do that? Thank you for you support.

"""
Bank with multiple queues example
Covers:
- Resources: Resource
- Iterating processes
Scenario:
A multi-counter bank with a random service time and customers arrival process. Based on the
program bank10.py from TheBank tutorial of SimPy 2. (KGM)
By Aaron Janeiro Stone
"""
from simpy import *
import random
maxNumber = 30      # Max number of customers
maxTime = 400.0     # Rumtime limit
timeInBank = 20.0   # Mean time in bank
arrivalMean = 10.0  # Mean of arrival process
seed = 12345        # Seed for simulation
def Customer(env, name, counters):
arrive = env.now
Qlength = [NoInSystem(counters[i]) for i in range(len(counters))]
print("%7.4f %s: Here I am. %s" % (env.now, name, Qlength))
for i in range(len(Qlength)):
if Qlength[i] == 0 or Qlength[i] == min(Qlength):
choice = i  # the chosen queue number
break
with counters[choice].request() as req:
# Wait for the counter
yield req
wait = env.now - arrive
# We got to the counter
print('%7.4f %s: Waited %6.3f' % (env.now, name, wait))
tib = random.expovariate(1.0 / timeInBank)
yield env.timeout(tib)
print('%7.4f %s: Finished' % (env.now, name))
def NoInSystem(R):
"""Total number of customers in the resource R"""
return max([0, len(R.put_queue) + len(R.users)])
def Source(env, number, interval, counters):
for i in range(number):
c = Customer(env, 'Customer%02d' % i, counters)
env.process(c)
t = random.expovariate(1.0 / interval)
yield env.timeout(t)
# Setup and start the simulation
print('Bank with multiple queues')
random.seed(seed)
env = Environment()
counters = [Resource(env), Resource(env)]
env.process(Source(env, maxNumber, arrivalMean, counters))
env.run(until=maxTime)

added a function to load the queues with customers before the bank opens which is time 0.

"""
Bank with multiple queues example
Covers:
- Resources: Resource
- Iterating processes
Scenario:
A multi-counter bank with a random service time and customers arrival process. Based on the
program bank10.py from TheBank tutorial of SimPy 2. (KGM)
By Aaron Janeiro Stone
"""
from simpy import *
import random
qStartNum = 20      # number of people in queue at start
maxNumber = 30      # Max number of customers after start
maxTime = 400.0     # Rumtime limit
timeInBank = 20.0   # Mean time in bank
arrivalMean = 10.0  # Mean of arrival process
seed = 12345        # Seed for simulation
def Customer(env, name, counters):
arrive = env.now
Qlength = [NoInSystem(counters[i]) for i in range(len(counters))]
print("%7.4f %s: Here I am. %s" % (env.now, name, Qlength))
for i in range(len(Qlength)):
if Qlength[i] == 0 or Qlength[i] == min(Qlength):
choice = i  # the chosen queue number
break
with counters[choice].request() as req:
# Wait for the counter
yield req
wait = env.now - arrive
# We got to the counter
print('%7.4f %s: Waited %6.3f' % (env.now, name, wait))
tib = random.expovariate(1.0 / timeInBank)
yield env.timeout(tib)
print('%7.4f %s: Finished' % (env.now, name))
def NoInSystem(R):
"""Total number of customers in the resource R"""
return max([0, len(R.put_queue) + len(R.users)])
def Source(env, minNumber, maxNumber, interval, counters):
for i in range(minNumber, maxNumber):
c = Customer(env, 'Customer%02d' % i, counters)
env.process(c)
t = random.expovariate(1.0 / interval)
yield env.timeout(t)
def preSource(env, number, counters):
"""
Queues customers before bank opens
"""
for i in range(number):
c = Customer(env, 'Customer%02d' % i, counters)
env.process(c)
# Setup and start the simulation
print('Bank with multiple queues')
random.seed(seed)
env = Environment()
counters = [Resource(env), Resource(env)]
preSource(env, qStartNum, counters)
env.process(Source(env, qStartNum, qStartNum + maxNumber, arrivalMean, counters))
env.run(until=maxTime)